Stock Grouping Based on Price Earnings Ratio and Price Book Value Using K-Medoids Algorithm

Muhammad Oemar Abdillah; Raissa Amanda Putri

doi:10.51519/journalisi.v6i3.809

Muhammad Oemar Abdillah State Islamic University of North Sumatra, Indonesia
Raissa Amanda Putri State Islamic University of North Sumatra, Indonesia

DOI: 10.51519/journalisi.v6i3.809

Keywords: Investment, K-Medoids, Clustering, Information System

Abstract

Investing involves allocating funds to achieve optimal returns by evaluating opportunities and managing risks in asset acquisition. Recently, many news reports have highlighted issues in the Indonesian capital market, such as stock investors using online loan funds for trading, which often leads to debt. This research aims to apply the K-Medoids algorithm for stock clustering, enabling investors to select fundamentally sound stocks based on the Price-Earnings Ratio (PER) and Price-Book Value (PBV). The K-Medoids method results show that Cluster 1 includes 93 stocks with moderate PER and PBV values. Cluster 2 comprises 91 stocks with the lowest PER and PBV values. Cluster 3 contains 113 stocks with the highest PER and PBV values. Developing an information system that classifies stocks based on PER and PBV can help investors analyze and make investment decisions more effectively.

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